exploring information quality in accounting information...

IBIMA Publishing

Communications of the IBIMA

http://www.ibimapublishing.com/journals/CIBIMA/cibima.html

Vol. 2011 (2011), Article ID 683574, 12 pages

DOI: 10.5171/2011.683574

Copyright © 2011 Manirath Wongsim and Jing Gao. This is an open access article distributed under the

Creative Commons Attribution License unported 3.0, which permits unrestricted use, distribution, and

reproduction in any medium, provided that original work is properly cited. Contact author: Manirath

Wongsim e-maill: [email protected].

Exploring Information Quality in

Accounting Information Systems Adoption

Manirath Wongsim and Jing Gao

School of Computer and Information Science, University of South Australia, Mawson Lakes, Australia

______________________________________________________________________________________________________________

Abstract

Information Quality (IQ) Management plays a vital role in the process of Accounting

Information Systems (AIS) adoption. IQ is emerging as a well-known business problem in

modern organisations. Specifically, the level of information quality is critical for all accounting

processes, and has a significant impact on business decision-making. It must be noted that

modern organisations rely heavily on the use of accounting information systems for their

accounting processes. There is a growing need for research to provide insights into issues and

solutions related to IQ in AIS adoption. This research aims to explore ways of managing

information quality and AIS adoption to investigate the relationship between the IQ issues and

AIS adoption process. This study has led to the development of a framework to guide the

organisations on implementing an adequate IQ management approach during the system

adoption process. This research was done on 44 respondents at ten organisations within

manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that

IQ dimensions in AIS adoption provide assistance in all processes of decision making. This

research provides empirical evidence that information quality of AIS adoption affect decision

making and suggests that these variables should be considered in adopting AIS in order to

improve the effectiveness of AIS.

Keywords: Information Quality, Information Quality Dimensions, Accounting Information

Systems, Accounting Information System Adoption.

__________________________________________________________________________

Introduction

Nowadays, information is one of the main

resources used and applied in

organisations. Information development is

essential for improving or developing new

contexts to support management, strategy,

and decision making (Lee, Strong et al.

2002; Michnik and Lo 2009; Salaün and

Flores 2001). Furthermore, management

information is important in organisations

as it requires quality information, to

improve the efficiency and effectiveness of

their operations for higher profitability and

increased productivity. For significant

business decision-making, Information

Quality (IQ) has become an important

consideration for any organisation that

wants to perform a variety of tasks well.

Information Quality refers to the capability

of data to be fit for use.

There is a strong evidence that IQ issues

have become a critical concern for

organisations (Lee, Strong et al. 2002;

Michnik and Lo 2009). Salaun and Flores

(2001) indicate that, currently, customers

require good quality information which is

basic to the requirements of business

activity and lead to high quality work

performance in the partnership between

supplier and consumer. According to Lee,

Communications of the IBIMA 2

Strong et al (2002), the growth of data

warehouses has increased the need for

quality data in order for organisations to

perform well, obtain competitive

advantage, and survive in today’s global

economy. Thus, data management is

important in organisations, in order to

support and develop different departments

in corporations by enabling work

processes of all sorts, as well as decision-

making.

In particular, accounting is essential in

making economic decisions. Furthermore,

accounting and management decision-

making is dependent on the fit of the

Accounting Information Systems (AIS) with

the organisation’s requirements.

Therefore, organisations must pay

attention to the efficiency of their

accounting information systems. In order

to implement AIS successfully, it is

important to address the quality of

information adoption, to manage all the

processes of accounting systems. Thus, this

research intends to study this perspective

of IQ management in AIS adoption.

Background

Information quality problems can impact

on operations, increase costs and lower

worker job-satisfaction, while increasing

customer dissatisfaction (Redman 1998).

In a modern world, information quality is

potent in that it directs the business’s

future. This is because good information

quality can lead to success while poor

information quality can lead to failure of

the business (Bovee 2004; Redman 1998;

Redman 2008). Consequently, information

quality criteria have become important

considerations for any organisation that

wants to carry out a variety of processes

well.

In particular, accounting and management

decision-making are concerned with the

appropriateness of the AIS for the

organisation’s requirements for

information communication and control

(Gordon and Miller 1976; McLaney and

Atrill 2005). The argument behind this

finding is that accounting information

systems often lack high-quality data.

Likewise, Ismail and King (2005) find that

organisations may lack knowledge and the

vision to incorporate accounting

information systems; additionally, there

are still problems in the process of

accounting implementation. However,

business needs to be seen as a system using

accounting information well, requiring

quality data in organisations to perform

well, obtain competitive advantage, and

survive in today’s global economy. These

are all critical to a company in order to

organise, manage and operate processes in

all sections. Furthermore, organisational

structure is important to improving or

adopting AIS systems. A well-managed,

well-designed accounting system can

improve work performance and increase

the efficiency of activities in accounting

responsibility.

Findings from the literature indicate that

an AIS is a specific software application and

management process. Kaplan (1998)

indicates that enterprises should operate

management accounting outside the ERP

system because the same system cannot

provide information for financial

accounting. What’s more, Malmi (2001)

and Scapens and Jazayeri (2003) Find that

the relationship between ERP systems and

management accounting techniques have

not changed significantly. However, while

ERP systems are considered to be

important data sources for most new

accounting practises, they are not an

incentive for accounting techniques and

system adoption. The characteristics of

accounting techniques are different in a

number of elements. Moreover, Rom and

Rohde (2007) indicate that data integration

in accounting should be studied more

narrowly (Rom and Rohde 2007). Other

authors (e.g. Davila, Foster et al, 2004;

Naomi and Kevin, 2007; Ismail, 2009;

Romney and Steinbart, 2009) state that

within organisations there must be

attention given to the accounting standards

and laws of each country.

Recently, when adopting AIS, some

organisations used AIS vendors for

adopting accounting systems developed by

the software vendors for the organisations

who want to adopt their solutions. Other

3 Communications of the IBIMA

organisation adopted generic frameworks

developed by COBIT, ITIL, and SDLC as

guidelines on how to select and adopt AIS

systems, even though not specific for AIS

adoption.

Most of the research concerning AIS has

focused on the management of internal

controls, design of an accounting

information system and auditing (Choe

2004; Nicolaou 2000). Few studies have

attempted to understand how to choose

and use (adopt) AIS systems well, in

organisations, to meet all IQ requirements.

In order to ensure information quality in

AIS adoption, it is important to understand

the underlying appropriate IQ criteria

specifically for AIS adoption. However, no

standard definition exists today; although

there have been some studies of qualitative

characteristics in accounting quality

management, such as FASB, IASB, AARF,

and SAC3. Some of the IQ literature also

addresses the critical points and steps for

adopting IQ systems.

Interestingly, IQ management specific to

AIS adoption is a new area; there is a

growing need for research to provide

insight into issues and solutions related to

IQ management in AIS adoption. A number

of generic IQ frameworks have been

proposed in the literature, but none of

them has actually looked into the area of

AIS adoption. There is a lack of knowledge

and of a standards framework for

information quality management in

accounting information systems adoption

that can assist organisations to ensure and

improve accounting information quality.

Thus, this research tries to develop an

adequate framework to provide such

guidance.The framework is developed

based upon the existing literature review

and multiple case studies. The framework

has been designed to illustrate IQ issues in

AIS adoption. It also attempts to identify

the critical success factors that

organisations should focus on, to ensure IQ

during the systems adoption process.

Framework for Information Quality Management in Accounting Information Systems

Adoption

Fig 1. IQ Management in AIS Adoption Framework (Source: Developed by the authors)

The research framework for this study is

presented in Fig 1. The framework posits

that accounting information systems

adoption is affected by internal and

external organisations and also requires

quality information in order to function

effectively. Moreover, accounting and

management decision making are

concerned with the appropriateness of the

AIS for the organisation’s requirements for

information communication and control. In

order to adopt AIS successfully, it is

important to consider the quality of the

system and the quality of information used

throughout the adoption process (Delone

and McLean 2003; Nelson and Todd 2005).

Likewise, information quality dimensions

influence the advantage of AIS adoption.

This is because information quality

dimensions utilised in AIS adoption can

help organisations to understand the

requirements for delivering high quality

information. Furthermore, accounting

systems adoption requires quality

information in order to function effectively,

where the level of information quality is


critical for all accounting system processes.

Information quality dimensions are

relevant to all data management processes

adopted by an organisation. Thus,

organisations need to apply information

criteria to organize and control all stages of

AIS and AIS adoption. This framework links

IQ management efforts to AIS adoption

performance. The framework is developed

based upon the existing literature and the

exploratory multiple case study, discussed

in detail in the next sections.

Research Methodology

This research used qualitative, interpretive

evidence. Interpretive research often

involves using qualitative methods from

which to develop awareness gained from

the data collection, and analyses the

research process (Avison and Myers 2002;

Orlikowski and Baroudi 1991). In this

study, collecting relevant information was

done by conducting interviews following

initial exploratory work. Literature reviews

were used together with a conceptual

study research method in order to develop

interview questions.

Furthermore, this study used case studies

in ten organisations as confirmatory

evidence. The selection of cases in this

study was purposefully carried out in order

to achieve theoretical and literal

replication. Cases were selected on the

basis of three dimensions: industry type,

and the size and type of organisation.

Regarding the first dimension, there are

different types of business - agricultural,

financial, industrial, education and

government. The second dimension relates

to organisation sectors, consisting of public

and private groups. The third dimension

focuses on the size of various

organisations, especially large corporations

and SMEs. The selected organisations are

from Thailand but enable the dimensions

to be addressed.

Case studies were used to provide useful

insights into the nature of IQ issues when

adopting AIS. This study used in-depth

interviews to collect information as well as

involving semi-structured interviews and

unstructured interviews with stakeholders

such as:

• Data producers who create, collect and

monitor information for AIS.

• Data auditors who record, classify, report

and interpret financial information.

• Data analysts who analyse, design,

develop and operate AIS adoption.

• Data users who access and operate AIS in

their work activities.

• Data managers who are responsible for

managing and controlling information

and information quality in AIS adoption.

Moreover, data collection sources also

included relevant documents, such as

position descriptions, policy manuals,

organisational charts, service records, and

annual reports. The purpose of the case

studies was to investigate what was an

appropriate IQ issue associated with AIS

adoption and how best to choose and use

an AIS adoption in organisations,

considering factors before and during the

adoption of an AIS. Moreover, the

qualitative data analysis methods used

included pattern-matching, content

analysis, and cross-case synthesis.

Research Finding

IQ Dimensions in AIS Adoption

In this research, IQ dimensions are

identified as relevance, reliability,

comparability, understandability,

availability, effectiveness, efficiency,

confidentiality, accessibility, integrity,

compliance, accuracy, objectivity, security,

completeness, and timeliness, as identified

from the literature and business

requirements from information in the

multiple case studies. These information

quality dimensions are relevant to all data

management processes adopted by

organisations, as show in Fig 2. The results

of IQ dimensions in AIS adoption, all

variables in this study, were measured by

in-depth interviews. Furthermore, the

research summarises the scores given by

different stakeholders in Case A to Case J

(the ten organisations).


Fig 2. Result of IQ Dimension form Multiple Case Studies

(Source: Developed by the authors)

Legend: 1, 2, 3, 4, 5 = Rating of the importance [never=1, rarely=2, sometime=3, often=4,

always=5]

Fig 2 presents the results of IQ dimensions

in AIS adoption from sixteen dimensions

among the 44 respondents. Respondents

were asked to indicate on a scale of five

choices consisting of never agree, rarely

agree, sometime agree, often agree, and

always agree. Thai listed organisations

have score of 5.00 for IQ dimensions such

as Accuracy, Effectiveness, Efficiency,

Relevance, Reliability and Timeline; the

firms have a score of 4.00 for all IQ

dimensions; a score of 3.00 for IQ

dimensions including Accessibility,

Availability, Comparability, Completeness,

Relevance, Reliability, Security, and

Understandability; a score of 2.00 for IQ

dimensions of Comparability and

Understandability; a score of less than 2.00

for any IQ dimension was not revealed by

the results.

One of the interviewees illustrated the

significance of positive relationships

between the performance of an AIS

adoption and IQ dimensions in the AIS

system. The CEO noted that:

“I think organisations need to satisfy the

quality, reliability and security requirements

for our information, as for all assets. We

need for available IT resources, including

applications, information, infrastructure

and people to drive business goals. In ours

organisation identifies to satisfy business

goals by used information quality dimension

to control accounting information systems

and AIS adoption. We have been described

by information dimension including

Accessibility, Accuracy, Availability,

Completeness, Compliance, Confidentiality,

Effectiveness, Efficiency, Integrity,

Objectivity, Relevance, Reliability, Security,

Timeline and Understandability in all

adoption process”.

CEO (Company A)

Company A used information quality

criteria to successfully adopt AIS. They

used information criteria to control all

stages of the AIS adoption process for

checking the system. Organisation A aimed

to define requirements for IQ criteria, and

then applied requirements management

and requirements analysis to control and

improve all processes within AIS adoption.

Moreover, they are concerned about the

root causes of IQ problems and aim to

determine the impact of poor IQ. Most

importantly, the project manager is

responsible for all IQ management efforts

to improve quality of information in

decision making for the acquired AIS

system. This company needs to be seen as

effectively adopting AIS, meeting the

required quality of accounting information.


In addition, the IT manager in company B

believes that the AIS are important in

helping organisations to make profits.

Company B was also concerned to identify

that IQ dimensions help to ensure

alignment to business requirements. As

one of the interviewees indicated:

“In our organisation, we have been

information quality dimensions to control

work processes refer to as business process

and AIS process for information quality such

as Reliability, Confidentiality, Accuracy,

Availability, Integrity, Compliance,

Accessibility, Security, Comprehensiveness,

Relevance, Effectiveness, Efficiency,

Timeline, Comparability, Understandability.

IQ dimensions can help organisation to

managing and controlling information to

satisfy business objective. What is more, the

company would like to conduct the IQ

dimension checks before moving accounting

data into the new system. We have been

satisfying AIS system and can help ours a lot

to operate work performances”.

IT Manager (Company B)

Company B believes that IQ dimensions

help to ensure configuration to business

requirements. Especially, they have to

check the IQ dimensions during the

change-over process to make sure data is

moved into the new system with a high

level of information quality. Furthermore,

the organisation uses continuous IQ

management such as IQ threats

management, business process for IQ

improvement, develop IQ management and

IQ management improvement. The

organisation has strict governance of IQ

policies, IQ benchmarks, IQ planning, IQ

Audit and provides accountability and

rewards. In addition, organisation B

considered IQ dimensions, such as AIS

adoption processes, by using the IQ

dimensions to check all processes to

ensure AIS performance and providing IT

governance in the organisation.

Another case study organisation also had a

group of personnel who indicate that:

“We’re using IQ criteria to control all work

process in our organisation. So our systems

have been some problem but overall [we’re]

satisfied. We have been using IQ criteria

including Availability, Compliance,

Confidentiality, Effectiveness, Efficiency,

Integrity, Reliability as business policy and

objective. Do you think they are

appropriate? I think they are appropriate

but should improve to high work

performance.”

Accounting Manager and director of IT

(CompanyE)

Company E has controls embedded in

business processes, IT processes and

services, by adopting IQ criteria. In

implementing AIS successfully, all stages

have been concerned with information

quality issues to improve the AIS adoption

in the organisation. This approach covers

strategy and tactics, and concerns the

identification of the ways IT can best

contribute to the achievement of the

business objectives. In addition, the

organisation has been using continuous IQ

management such as Developing IQ

implementation, Implementing IQ Project,

and IQ management governance. Moreover,

this company uses IQ criteria to support IT

objectives and to measure them within the

process employed to achieve the required

performance.

AIS Adoption Processes

Fig 3 shows a summary of case studies’ AIS

Adoption process findings from multiple

case studies by different types of business -

agricultural, financial, industrial, education

and government. The selection of cases in

this study was purposefully carried out in

order to achieve theoretical and literal

replication. The number of cases may

depend on the purpose of research,

available resources and constraints; in

addition, the decision about the number of

cases may be left to the individual

researcher (Patton 1990). For the

remaining factors, although to some extent

conflicts still existed across cases,

agreement seems greater than the

differences.


Fig 3. AIS Adoption Processes Model (Source: Developed by the authors)

The Factors in Red Denote the New Factors that are Finding from Case Studies

Fig 3 shows that adopting AIS involves

using technology-adoption to support

operations, strategic management, and

decision-making in the firm. A well-

managed and designed AIS adoption

process can improve AIS performance and

increase the efficiency of activities as well

as help organisations to make profits by

improving the quality and reducing the

cost of products or services, sharing

knowledge and improved decision-making

(Romney, Marshall B 2009). The model

reference framework deFines 41 high-level

control objectives for AIS adoption

processes.

One of the interviewees identified the

performance of an AIS adoption as most

important in accounting activities. The

director of the IT department noted that:

“We often are using 40 steps to manage and

guidelines on how to develop new system

depend on project and each system as

development. Developing AIS includes 40

steps that include Define a requirement,

Identifies root cause of IQ problem and

determine impact of poor IQ, determine the

technology direction, Identify data quality

requirement, Requirement analysis, Manage

Project and mange investment, Find vendor

or IT Support, Communicate management

aims and direction, Manage Quality, Manage

team work to support project, System

Design, Acquire and maintain application

software, Acquire and maintain application

maintain infrastructure, Develop IQ

Implementation, IQ management

Improvement, Implementing, Install and

accredit solution and manage changes,

Procure IT resources, Manage data profiling

and data cleansing, Integration and Test, IQ

management governance, Define and

manage service levels, data quality

improvement, Educate and train users,

Ensure continuous service, Ensure system

security, Manage operations, Manage

performance and capacity, Manage

problems, Manage service desk and

incidents, Manage the configurations,

Manage the physical environment, Manage

third-party services, Support and

Maintenance, Manage data, Monitor and

evaluate internal control, Monitor and

evaluate IT performance, Provide IT

governance, IQ insurance and control, IQ

monitors and evaluates. We have [to] check

all processes before used accounting

software upon IQ polices and also approval

from board of organisation. We have been

satisfy system this AIS system can help

employee activity and work performance”

Director of IT department (Company B)


Company B used AIS vendor for

implementing its accounting systems and

also adopted some accounting software

modules as they could buy the software

and then modify it themselves to use in the

company.

Another case study organisation also had a

large group of personnel who indicate that:

“This company seen as IQ has been

important in acquire and implement AIS and

using to control all stage adopting AIS

process. Moreover, we have been deCines 40

high-level control objectives for IT adoption

processes that are described as Define a

requirement, Identifies root cause of IQ

problem and determine impact of poor IQ,

determine the technology direction, Identify

data quality requirement, Requirement

analysis, Manage Project and mange

investment, Find vendor or IT Support,

Communicate management aims and

direction, Manage Quality, Manage team

work to support project, System Design,

Acquire and maintain application software,

Acquire and maintain application maintain

infrastructure, Develop IQ Implementation,

IQ management Improvement,

Implementing, Install and accredit solution

and manage changes, Manage data profiling

and data cleansing, Integration and Test, IQ

management governance, Implementing IQ

Project, Define and manage service levels,

data quality improvement, Educate and

train users, Ensure continuous service,

Ensure system security, Manage operations,

Manage performance and capacity, Manage

problems, Manage service desk and

incidents, Manage the configurations,

Manage the physical environment, Manage

third-party services, Support and

Maintenance, Manage data, Monitor and

evaluate internal control, Monitor and

evaluate IT performance, Provide IT

governance, IQ insurance and control, IQ

monitors and evaluates. We believe system

can help improve our work. In addition,

acquire and implement AIS relation to

accounting information systems that

important in an organisation, for it to

become effective in business, decision

making and growing business.”

Director of IT audit division (Company E)

Company E employed wide

implementation of a new accounting

system supplied by the AIS vendor in order

to implement accounting systems.

Moreover, some modules can use their

information systems to develop in-house

software within the organisation, or

companies may buy software and then

modify it themselves to use in the

company.

Managing the IQ Dimensions into the AIS

Adoption Process

This research shows that, in developing

accounting information systems,

information quality management has the

potential to influence decision making in

each process of AIS adoption. Moreover,

this study indicates that IQ dimensions

have a positive relationship with AIS

adoption processes. Table 1 shows ways of

mapping the IQ dimensions into individual

adoption stages using findings from the

case studies. Within the adoption processes

of AIS, AIS system selection which provides

direction to solutions for the delivery of

AIS system implementation is included.

The AIS system implementation provides

the solutions and passes them on, to be

turned into services, receives the solutions,

and makes them usable for end users. The

AIS system use monitors for all processes

to ensure that the direction is satisfied. In

order to ensure that the AIS requirements

for information quality are met, adequate

control measures need to be defined,

adopted and monitored over these

resources.

AIS System Selection

The first stage is concerned with

information quality issues to improve the

AIS adoption in an organisation. This stage

can help organisations to define a strategic

IT plan. It covers strategy and tactics, and

concerns the identification of the ways in

which IT can best contribute to the

achievement of the accounting objectives

as business needs. Furthermore,

organisations require defined

requirements IQ criteria, requirements

management, requirements analysis for


control and to improve all processes of AIS

adoption (shown in table1). They are also

concerned about the root causes of IQ

problems and determine the impact of

poor IQ. Most importantly, the project

manager is responsible for all IQ

management efforts to improve quality of

information in decision making for the

acquired AIS system.

AIS System Implementation

The second stage helps an organisation to

identify IT development. To realise an IT

strategy, IT solutions need to be identified,

developed or acquired, as well as

implemented and integrated into the

business processes. Moreover, changes in

and maintenance of existing systems are

covered by this stage to make sure the

solutions continue to meet accounting

objectives as business requirements. In

addition, organisations must maintain

continuous IQ management such as IQ risks

management, IQ management cost

advantage, accounts process for IQ

improvement, IQ metrics management.

Moreover, organisations must have strict

governance of IQ roles, IQ benchmarks, IQ

strategies, and the IQ Audit.

AIS System Use

Stage three addresses IT operations and is

concerned with the actual delivery of

required services. This incorporates the

need to monitor operations, and addresses

managing performance, monitoring of

internal control, complaint regulatory

procedures and providing governance.

Distinguishing IQ dimensions in this way

can help information producers and users

understand the requirements for delivering

high quality information by IQ insurance

and control, IQ monitors and evaluations,

and IQ governance.


Table 1: Mapping IQ Dimension into Individual AIS Adoption Stage

IQ dimensions

Re

lev

an

ce

Re

lia

bil

ity

Co

mp

ara

bil

ity

Eff

ec

tiv

en

es

s

Eff

icie

ncy

Co

nfi

de

nti

ali

ty

Av

ail

ab

ilit

y

Inte

gr

ity

Co

mp

lia

nce

Un

de

rst

an

da

bil

it

y

Ac

cu

ra

cy

Ob

jec

tiv

ity

Ac

ce

ss

ibil

ity

Se

cu

rit

y

Co

mp

lete

ne

ss

Tim

eli

ne

AIS process

1. DeFine requirement √ √ √ 2. IdentiFies root cause of IQ problem and

determine impact √ √ √ √ √ 3. Determine the technological direction. √ √ 4. Identify data quality requirement √ √ 5. Requirement analysis √ √ √ √ √ √ √ 6. Manage projects and manage Investment √ √ √ 7. Find vendor and IT resources. √ √ √ √ √ 8.Communicate management aims and

direction. √ √ 9. Manage quality. √ √ √ √ √ √ √ 10. Manage team work to support project √ √ 11. Design System √ √ √ √ √ √ 12.Acquire and maintain application

software. √ √ √ √ √ √ √ 13.Acquire and maintain infrastructure √ √ √ √ √ √ √ 14.Develop IQ Implement √ √ √ √ √ √ √ 15. IQ management improvement √ √ √ √ √ √ √ 16. Implementing √ √ √ √ √ √ √ 17.Install and accredit solutions and

changes. √ √ √ √ √ √ √ 18. Procure IT resources. √ √ √ 19. Manage data proFiling and data cleansing √ √ √ √ √ √ √ 20.System integration and Testing √ √ √ √ √ √ √ 21. Implement IQ Project √ √ √ √ √ √ √ 22. IQ management governance √ √ √ √ √ √ √ 23. DeFine and manage service levels. √ √ √ √ √ √ √ 24. Data quality improvement √ √ √ √ √ 25. Educate and train users. √ √ √ 26. Ensure continuous service. √ √ √ 27. Ensure systems security. √ √ √ √ √ √ √ 28. Manage operations. √ √ √ √ √ √ √ √ 29. Manage performance and capacity. √ √ √ √ √ 30. Manage problems. √ √ √ √ √ √ √ 31. Manage service desk and incidents. √ √ √ √ 32. Manage the conFigurations. √ √ √ √ 33. Manage the physical environment. √ √ √ 34. Manage third-party services. √ √ √ √ √ √ √ 35. Support and Maintenance √ √ √ √ √ 36. Manage data. √ √ √ √ √ 37. Monitor and evaluate internal control. √ √ √ √ √ √ √ √ √ √ √ 38. Monitor and evaluate IT performance. √ √ √ √ √ √ √ √ √ √ √ 39. Provide IT governance √ √ √ √ √ √ √ √ √ √ 40. IQ insurance and control √ √ √ 41. IQ monitors and evaluates √ √ √ √ √ √ √

(Source: Developed by the authors)


Discussion and Conclusions

This analysis was done on the data of 44

respondents, from ten organisations within

manufacturing firms in Thailand; data was

collected by in-depth interviews which

involved semi-structured interviews and

unstructured interviews. This research

provides empirical evidence that adopting

AIS information from internal or external

organisation requires recognition that

information quality affects decision-

making, suggesting that IQ dimensions

should be considered in developing AIS in

order to improve the effectiveness of AIS

systems. This study investigates

information quality dimensions in

accounting information systems adoption.

The framework measured IQ dimensions

from sixteen dimensions including

relevance, reliability, comparability,

understandability, availability,

effectiveness, efficiency, confidentiality,

accessibility, integrity, compliance,

accuracy, objectivity, security,

completeness, and timeliness for adopting

AIS. The level of importance of IQ

dimensions was measured by a five point

scale completed by the ten sample firms.

The level of AIS adoption process defines

41 high-level control objectives as show in

Fig 3. The overall results indicate that IQ

dimensions have a positive relationship

with AIS adoption processes. The evidence

in this study suggests that an IQ criterion

promotes AIS adoption process

performance. Furthermore, IQ dimensions

play a vital role in the process of AIS

adoption. This evidence suggests that

organisations should obtain knowledge of

appropriate information quality

dimensions for accounting information

systems adoption to improve work

performance as well as help organisations

to make profits.

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